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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13844

Title: Semiparametric estimation of conditional copulas
Authors: Abegaz, Fentaw
Gijbels, Irène
VERAVERBEKE, Noel
Issue Date: 2012
Publisher: ELSEVIER INC
Citation: JOURNAL OF MULTIVARIATE ANALYSIS, 110, p. 43-73
Abstract: The manner in which two random variables influence one another often depends on covariates. A way to model this dependence is via a conditional copula function. This paper contributes to the study of semiparametric estimation of conditional copulas by starting from a parametric copula function in which the parameter varies with a covariate, and leaving the marginals unspecified. Consequently, the unknown parts in the model are the parameter function and the unknown marginals. The authors use a local pseudo-likelihood with nonparametrically estimated marginals approximating the unknown parameter function locally by a polynomial. Under this general setting, they prove the consistency of the estimators of the parameter function as well as its derivatives : they also establish asymptotic normality. Furthermore, they derive an expression for the theoretical optimal bandwidth and discuss practical bandwidth selection via a simulation study and a real-data case.
Notes: [Abegaz, Fentaw; Gijbels, Irene] Katholieke Univ Leuven, Dept Math, Louvain, Belgium. [Abegaz, Fentaw; Gijbels, Irene] Katholieke Univ Leuven, Leuven Stat Res Ctr LStat, Louvain, Belgium. [Abegaz, Fentaw] Univ Addis Ababa, Addis Ababa, Ethiopia. [Veraverbeke, Noel] Univ Hasselt, Ctr Stat, Hasselt, Belgium. irene.gijbels@wis.kuleuven.be
URI: http://hdl.handle.net/1942/13844
DOI: 10.1016/j.jmva.2012.04.001
ISI #: 000305817500005
ISSN: 0047-259X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2013
Appears in Collections: Research publications

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